Theodora Katsila

Personalized pharmacogenomics profiling using whole-genome sequencing

AIM Pharmacogenomics holds promise to rationalize drug use by minimizing drug toxicity and at the same time increase drug efficacy. There are currently several assays to screen for known pharmacogenomic biomarkers for the most commonly prescribed drugs. However, these genetic screening assays cannot account for other known or novel pharmacogenomic markers. MATERIALS & METHODS We analyzed whole-genome sequences of 482 unrelated individuals of various ethnic backgrounds to obtain their personalized pharmacogenomics profiles. RESULTS Bioinformatics analysis revealed 408,964 variants in 231 pharmacogenes, from which 26,807 were residing on exons and proximal regulatory sequences, whereas 16,487 were novel. In silico analyses indicated that 1012 novel pharmacogene-related variants possibly abolish protein function. We have also performed whole-genome sequencing analysis in a seven-member family of Greek origin in an effort to explain the variable response rate to acenocoumarol treatment in two family members. CONCLUSION Overall, our data demonstrate that whole-genome sequencing, unlike conventional genetic screening methods, is necessary to determine an individuals pharmacogenomics profile in a more comprehensive manner, which, combined with the gradually decreasing whole-genome sequencing costs, would expedite bringing personalized medicine closer to reality.

Computational approaches in target identification and drug discovery

In the big data era, voluminous datasets are routinely acquired, stored and analyzed with the aim to inform biomedical discoveries and validate hypotheses. No doubt, data volume and diversity have dramatically increased by the advent of new technologies and open data initiatives. Big data are used across the whole drug discovery pipeline from target identification and mechanism of action to identification of novel leads and drug candidates. Such methods are depicted and discussed, with the aim to provide a general view of computational tools and databases available. We feel that big data leveraging needs to be cost-effective and focus on personalized medicine. For this, we propose the interplay of information technologies and (chemo)informatic tools on the basis of their synergy.

Deciphering next-generation pharmacogenomics: an information technology perspective

In the post-genomic era, the rapid evolution of high-throughput genotyping technologies and the increased pace of production of genetic research data are continually prompting the development of appropriate informatics tools, systems and databases as we attempt to cope with the flood of incoming genetic information. Alongside new technologies that serve to enhance data connectivity, emerging information systems should contribute to the creation of a powerful knowledge environment for genotype-to-phenotype information in the context of translational medicine. In the area of pharmacogenomics and personalized medicine, it has become evident that database applications providing important information on the occurrence and consequences of gene variants involved in pharmacokinetics, pharmacodynamics, drug efficacy and drug toxicity will become an integral tool for researchers and medical practitioners alike. At the same time, two fundamental issues are inextricably linked to current developments, namely data sharing and data protection. Here, we discuss high-throughput and next-generation sequencing technology and its impact on pharmacogenomics research. In addition, we present advances and challenges in the field of pharmacogenomics information systems which have in turn triggered the development of an integrated electronic ‘pharmacogenomics assistant’. The system is designed to provide personalized drug recommendations based on linked genotype-to-phenotype pharmacogenomics data, as well as to support biomedical researchers in the identification of pharmacogenomics-related gene variants. The provisioned services are tuned in the framework of a single-access pharmacogenomics portal.

A European spectrum of pharmacogenomic biomarkers: Implications for clinical pharmacogenomics

Pharmacogenomics aims to correlate inter-individual differences of drug efficacy and/or toxicity with the underlying genetic composition, particularly in genes encoding for protein factors and enzymes involved in drug metabolism and transport. In several European populations, particularly in countries with lower income, information related to the prevalence of pharmacogenomic biomarkers is incomplete or lacking. Here, we have implemented the microattribution approach to assess the pharmacogenomic biomarkers allelic spectrum in 18 European populations, mostly from developing European countries, by analyzing 1,931 pharmacogenomics biomarkers in 231 genes. Our data show significant inter-population pharmacogenomic biomarker allele frequency differences, particularly in 7 clinically actionable pharmacogenomic biomarkers in 7 European populations, affecting drug efficacy and/or toxicity of 51 medication treatment modalities. These data also reflect on the differences observed in the prevalence of high-risk genotypes in these populations, as far as common markers in the CYP2C9, CYP2C19, CYP3A5, VKORC1, SLCO1B1 and TPMT pharmacogenes are concerned. Also, our data demonstrate notable differences in predicted genotype-based warfarin dosing among these populations. Our findings can be exploited not only to develop guidelines for medical prioritization, but most importantly to facilitate integration of pharmacogenomics and to support pre-emptive pharmacogenomic testing. This may subsequently contribute towards significant cost-savings in the overall healthcare expenditure in the participating countries, where pharmacogenomics implementation proves to be cost-effective.

Assessment of the Pharmacogenomics Educational Environment in Southeast Europe

Background/Aims: Pharmacogenomics aims to use the information derived from an individuals genomic profile in the context of individualizing medical treatment modalities. However, currently, pharmacogenomics education is not uniformly provided to health care professionals. This study investigates the status of pharmacogenomics education in Southeast Europe. Methods: University websites served as information sources in order to investigate the discrepancies in pharmacogenomics education in Southeast Europe. In parallel, a survey was conducted at the University of Cagliari (Italy) to test pharmacogenomics knowledge and understanding among specialists, residents and undergraduate students. Results: Our study shows that pharmacogenomics knowledge is not uniformly spread in universities in Southeast Europe and provides the basis for the harmonization of pharmacogenomics education that would directly impact on a smoother integration of pharmacogenomics into mainstream medical practice. Also, a considerable gap in pharmacogenomics education was obvious between the group of specialists and the groups of residents and undergraduate students. Conclusions: Pharmacogenomics education as well as the continuous enrichment of pharmacogenomics knowledge for health care professionals are fundamental approaches toward personalized medicine. Ideally, pharmacogenomics should be taught as a stand-alone course or at least in the context of genetics courses that already exist in universities in Southeast Europe.

DruGeVar: An Online Resource Triangulating Drugs with Genes and Genomic Biomarkers for Clinical Pharmacogenomics

Background/Aims: Pharmacogenomics aims to rationalize drug use by minimizing drug toxicity and/or by increasing drug efficacy. A large number of genomic markers have been correlated with variable drug responses and severity of adverse drug reactions. Although a number of these drugs bear pharmacogenomic information in their labels - approved by regulatory agencies - and comprehensive drug/gene lists exist online, information related to the respective pharmacogenomic biomarkers is currently missing from such lists. Methods: We extracted information from the published literature and online resources and developed DruGeVar (http://drugevar.genomicmedicinealliance.org), an online resource triangulating drugs with genes and pharmacogenomic biomarkers in an effort to build a comprehensive database that could serve clinical pharmacogenomics. Results and Conclusions: A user-friendly data querying and visualization interface allows users to formulate simple and complex queries. Such a database would be readily applicable as a stand-alone resource or a plug-in module for other databases.

Pharmacometabolomics-aided Pharmacogenomics in Autoimmune Disease

Inter-individual variability has been a major hurdle to optimize disease management. Precision medicine holds promise for improving health and healthcare via tailor-made therapeutic strategies. Herein, we outline the paradigm of “pharmacometabolomics-aided pharmacogenomics” in autoimmune diseases. We envisage merging pharmacometabolomic and pharmacogenomic data (to address the interplay of genomic and environmental influences) with information technologies to facilitate data analysis as well as sense- and decision-making on the basis of synergy between artificial and human intelligence. Humans can detect patterns, which computer algorithms may fail to do so, whereas data-intensive and cognitively complex settings and processes limit human ability. We propose that better-informed, rapid and cost-effective omics studies need the implementation of holistic and multidisciplinary approaches.

Meta-Analysis of Genes in Commercially Available Nutrigenomic Tests Denotes Lack of Association with Dietary Intake and Nutrient-Related Pathologies

Nutrigenomics is an emerging discipline that aims to investigate how individual genetic composition correlates with dietary intake, as well as how nutrition influences gene expression. Herein, the fundamental question relates to the value of nutrigenomics testing on the basis of the currently available scientific evidence. A thorough literature search has been conducted in PubMed scientific literature database for nutrigenomics research studies on 38 genes included in nutrigenomics tests provided by various private genetic testing laboratories. Data were subsequently meta-analyzed to identify possible associations between the genes of interest and dietary intake and/or nutrient-related pathologies. Data analysis occurred according to four different models due to data sparsity and inconsistency. Data from 524,592 individuals (361,153 cases and 163,439 controls) in a total of 1,170 entries were obtained. Conflicting findings indicated that there was a great incompatibility regarding the associations (or their absence) identified. No specific--and statistically significant-association was identified for any of the 38 genes of interest. In those cases, where a weak association was demonstrated, evidence was based on a limited number of studies. As solid scientific evidence is currently lacking, commercially available nutrigenomics tests cannot be presently recommended. Notwithstanding, the need for a thorough and continuous nutrigenomics research is evident as it is a highly promising tool towards precision medicine.

Whole genome sequencing in pharmacogenomics

Pharmacogenomics aims to shed light on the role of genes and genomic variants in clinical treatment response. Although, several drug–gene relationships are characterized to date, many challenges still remain toward the application of pharmacogenomics in the clinic; clinical guidelines for pharmacogenomic testing are still in their infancy, whereas the emerging high throughput genotyping technologies produce a tsunami of new findings. Herein, the potential of whole genome sequencing on pharmacogenomics research and clinical application are highlighted.

Individualizing fetal hemoglobin augmenting therapy for β-type hemoglobinopathies patients.

Individual genetic composition is an important cause of variations in the response and tolerance to drug treatment. Pharmacogenomics is a modern discipline aiming to delineate individual genomic profiles and drug response. To date, there are several medical disciplines where pharmacogenomics is readily applicable, while in others its usefulness is yet to be demonstrated. Recent experimental evidence suggest that besides genomic variation within the human β-globin gene cluster, other variants in modifier genes residing outside the human β-globin gene cluster are significantly associated with response to hydroxyurea treatment in β-type hemoglobinopathies patients, deducted from the increase in fetal hemoglobin levels. This article aims to provide an update and to discuss future challenges on the application of pharmacogenomics for β-type hemoglobinopathies therapeutics in relation to the current pharmacological treatment modalities for those disorders.